Differential Anti-Inflammatory Effects of Electrostimulation in a Standardized Setting.

The therapeutic usage of physical stimuli is framed in a highly heterogeneous research area, with variable levels of maturity and of translatability into clinical application. In particular, electrostimulation is deeply studied for its application on the autonomous nervous system, but less is known about the anti- inflammatory effects of such stimuli beyond the inflammatory reflex. Further, reproducibility and meta-analyses are extremely challenging, owing to the limited rationale on dosage and experimental standardization. It is specifically to address the fundamental question on the anti-inflammatory effects of electricity on biological systems, that we propose a series of controlled experiments on the effects of direct and alternate current delivered on a standardized 3D bioconstruct constituted by fibroblasts and keratinocytes in a collagen matrix, in the presence or absence of TNF-α as conventional inflammation inducer. This selected but systematic exploration, with transcriptomics backed by metabolomics at specific time points allows to obtain the first systemic overview of the biological functions at stake, highlighting the differential anti-inflammatory potential of such approaches, with promising results for 5 V direct current stimuli, correlating with the wound healing process. With our results, we wish to set the base for a rigorous systematic approach to the problem, fundamental towards future elucidations of the detailed mechanisms at stake, highlighting both the healing and damaging potential of such approaches.

Unlocking the Power of Human Ferritin: Enhanced Drug Delivery of Aurothiomalate in A2780 Ovarian Cancer Cells.

Aurothiomalate (AuTM) is an FDA-approved antiarthritic gold drug with unique anticancer properties. To enhance its anticancer activity, we prepared a bioconjugate with human apoferritin (HuHf) by attaching some AuTM moieties to surface protein residues. The reaction of apoferritin with excess AuTM yielded a single adduct, that was characterized by ESI MS and ICP-OES analysis, using three mutant ferritins and trypsinization experiments. The adduct contains ~3 gold atoms per ferritin subunit, arranged in a small cluster bound to Cys90 and Cys102. MD simulations provided a plausible structural model for the cluster. The adduct was evaluated for its pharmacological properties and was found to be significantly more cytotoxic than free AuTM against A2780 cancer cells mainly due to higher gold uptake. NMR-metabolomics showed that AuTM bound to HuHf and free AuTM induced qualitatively similar changes in treated cancer cells, indicating that the effects on cell metabolism are approximately the same, in agreement with independent biochemical experiments. In conclusion, we have demonstrated here that a molecularly precise bioconjugate formed between AuTM and HuHf exhibits anticancer properties far superior to the free drug, while retaining its key mechanistic features. Evidence is provided that human ferritin can serve as an excellent carrier for this metallodrug.

NMR Metabolomics of Primary Ovarian Cancer Cells in Comparison to Established Cisplatin-Resistant and -Sensitive Cell Lines.

Cancer cell lines are frequently used in metabolomics, such as in vitro tumor models. In particular, A2780 cells are commonly used as a model for ovarian cancer to evaluate the effects of drug treatment. Here, we compare the NMR metabolomics profiles of A2780 and cisplatin-resistant A2780 cells with those of cells derived from 10 patients with high-grade serous ovarian carcinoma (collected during primary cytoreduction before any chemotherapeutic treatment). Our analysis reveals a substantial similarity among all primary cells but significant differences between them and both A2780 and cisplatin-resistant A2780 cells. Notably, the patient-derived cells are closer to the resistant A2780 cells when considering the exo-metabolome, whereas they are essentially equidistant from A2780 and A2780-resistant cells in terms of the endo-metabolome. This behavior results from dissimilarities in the levels of several metabolites attributable to the differential modulation of underlying biochemical pathways. The patient-derived cells are those with the most pronounced glycolytic phenotype, whereas A2780-resistant cells mainly diverge from the others due to alterations in a few specific metabolites already known as markers of resistance.

Integrated Metabolomics and Proteomics of Symptomatic and Early Presymptomatic States of Colitis.

Colitis has a multifactorial pathogenesis with a strong cross-talk among microbiota, hypoxia, and tissue metabolism. Here, we aimed to characterize the molecular signature of the disease in symptomatic and presymptomatic stages of the inflammatory process at the tissue and fecal level. The study is based on two different murine models for colitis, and HR-MAS NMR on "intact" colon tissues and LC-MS/MS on colon tissue extracts were used to derive untargeted metabolomics and proteomics information, respectively. Solution NMR was used to derive metabolomic profiles of the fecal extracts. By combining metabolomic and proteomic analyses of the tissues, we found increased anaerobic glycolysis, accompanied by an altered citric acid cycle and oxidative phosphorylation in inflamed colons; these changes associate with inflammation-induced hypoxia taking place in colon tissues. Different colitis states were also characterized by significantly different metabolomic profiles of fecal extracts, attributable to both the dysbiosis characteristic of colitis as well as the dysregulated tissue metabolism. Strong and distinctive tissue and fecal metabolomic signatures can be detected before the onset of symptoms. Therefore, untargeted metabolomics of tissues and fecal extracts provides a comprehensive picture of the changes accompanying the disease onset already at preclinical stages, highlighting the diagnostic potential of global metabolomics for inflammatory diseases.

Fingerprinting and profiling in metabolomics of biosamples.

This review focuses on metabolomics from an NMR point of view. It attempts to cover the broad scope of metabolomics and describes the NMR experiments that are most suitable for each sample type. It is addressed not only to NMR specialists, but to all researchers who wish to approach metabolomics with a clear idea of what they wish to achieve but not necessarily with a deep knowledge of NMR. For this reason, some technical parts may seem a bit naïve to the experts. The review starts by describing standard metabolomics procedures, which imply the use of a dedicated 600 MHz instrument and of four properly standardized 1D experiments. Standardization is a must if one wants to directly compare NMR results obtained in different labs. A brief mention is also made of standardized pre-analytical procedures, which are even more essential. Attention is paid to the distinction between fingerprinting and profiling, and the advantages and disadvantages of fingerprinting are clarified. This aspect is often not fully appreciated. Then profiling, and the associated problems of signal assignment and quantitation, are discussed. We also describe less conventional approaches, such as the use of different magnetic fields, the use of signal enhancement techniques to increase sensitivity, and the potential of field-shuttling NMR. A few examples of biomedical applications are also given, again with the focus on NMR techniques that are most suitable to achieve each particular goal, including a description of the most common heteronuclear experiments. Finally, the growing applications of metabolomics to foodstuffs are described.

COVID-19: A complex disease with a unique metabolic signature.

Plasma of COVID-19 patients contains a strong metabolomic/lipoproteomic signature, revealed by the NMR analysis of a cohort of >500 patients sampled during various waves of COVID-19 infection, corresponding to the spread of different variants, and having different vaccination status. This composite signature highlights common traits of the SARS-CoV-2 infection. The most dysregulated molecules display concentration trends that scale with disease severity and might serve as prognostic markers for fatal events. Metabolomics evidence is then used as input data for a sex-specific multi-organ metabolic model. This reconstruction provides a comprehensive view of the impact of COVID-19 on the entire human metabolism. The human (male and female) metabolic network is strongly impacted by the disease to an extent dictated by its severity. A marked metabolic reprogramming at the level of many organs indicates an increase in the generic energetic demand of the organism following infection. Sex-specific modulation of immune response is also suggested.

Exploring the Effects of Probiotic Treatment on Urinary and Serum Metabolic Profiles in Healthy Individuals.

Probiotics are live microorganisms that confer health benefits when administered in adequate amounts. They are used to promote gut health and alleviate various disorders. Recently, there has been an increasing interest in the potential effects of probiotics on human physiology. In the presented study, the effects of probiotic treatment on the metabolic profiles of human urine and serum using a nuclear magnetic resonance (NMR)-based metabonomic approach were investigated. Twenty-one healthy volunteers were enrolled in the study, and they received two different dosages of probiotics for 8 weeks. During the study, urine and serum samples were collected from volunteers before and during probiotic supplementation. The results showed that probiotics had a significant impact on the urinary and serum metabolic profiles without altering their phenotypes. This study demonstrated the effects of probiotics in terms of variations of metabolite levels resulting also from the different probiotic posology. Overall, the results suggest that probiotic administration may affect both urine and serum metabolomes, although more research is needed to understand the mechanisms and clinical implications of these effects. NMR-based metabonomic analysis of biofluids is a powerful tool for monitoring host-gut microflora dynamic interaction as well as for assessing the individual response to probiotic treatment.

The effects of two cytotoxic gold(i) carbene compounds on the metabolism of A2780 ovarian cancer cells: mechanistic inferences through NMR analysis.

NMR metabolomics is a powerful tool to characterise the changes in cancer cell metabolism elicited by anticancer drugs. Here, the large metabolic alterations produced by two cytotoxic gold carbene compounds in A2780 ovarian cancer cells are described and discussed in comparison to auranofin, in the frame of the available mechanistic knowledge.

19F: A small probe for a giant protein.

Herein we describe a method for the efficient production (∼90% fluorination) of 5-F-Trp human H ferritin via the selective incorporation of 19F into the side chain of W93 using 5-fluoroindole as the fluorinated precursor of the amino acid. Human H ferritin is a nanocage composed of 24 identical subunits, each containing a single Trp belonging to a loop exposed on the external surface of the protein nanocage. This makes 5-F-Trp a potential probe for the study of intermolecular interactions in solution by exploiting its intrinsic fluorescence. More interestingly, albeit the large size of the cage (12 nm external diameter, ∼500 kDa molecular mass) we observe a broad but well defined NMR 19F resonance that can be used for the dual purpose of detecting solution intermolecular interactions via chemical shift perturbation mapping and monitoring the uptake of ferritin by cells treated with ferritin-based drug carriers, the latter being an application area of increasing importance.

Metabolic Robustness to Growth Temperature of a Cold- Adapted Marine Bacterium.

Microbial communities experience continuous environmental changes, with temperature fluctuations being the most impacting. This is particularly important considering the ongoing global warming but also in the "simpler" context of seasonal variability of sea-surface temperature. Understanding how microorganisms react at the cellular level can improve our understanding of their possible adaptations to a changing environment. In this work, we investigated the mechanisms through which metabolic homeostasis is maintained in a cold-adapted marine bacterium during growth at temperatures that differ widely (15 and 0°C). We have quantified its intracellular and extracellular central metabolomes together with changes occurring at the transcriptomic level in the same growth conditions. This information was then used to contextualize a genome-scale metabolic reconstruction, and to provide a systemic understanding of cellular adaptation to growth at 2 different temperatures. Our findings indicate a strong metabolic robustness at the level of the main central metabolites, counteracted by a relatively deep transcriptomic reprogramming that includes changes in gene expression of hundreds of metabolic genes. We interpret this as a transcriptomic buffering of cellular metabolism, able to produce overlapping metabolic phenotypes, despite the wide temperature gap. Moreover, we show that metabolic adaptation seems to be mostly played at the level of few key intermediates (e.g., phosphoenolpyruvate) and in the cross talk between the main central metabolic pathways. Overall, our findings reveal a complex interplay at gene expression level that contributes to the robustness/resilience of core metabolism, also promoting the leveraging of state-of-the-art multi-disciplinary approaches to fully comprehend molecular adaptations to environmental fluctuations. IMPORTANCE This manuscript addresses a central and broad interest topic in environmental microbiology, i.e. the effect of growth temperature on microbial cell physiology. We investigated if and how metabolic homeostasis is maintained in a cold-adapted bacterium during growth at temperatures that differ widely and that match measured changes on the field. Our integrative approach revealed an extraordinary robustness of the central metabolome to growth temperature. However, this was counteracted by deep changes at the transcriptional level, and especially in the metabolic part of the transcriptome. This conflictual scenario was interpreted as a transcriptomic buffering of cellular metabolism, and was investigated using genome-scale metabolic modeling. Overall, our findings reveal a complex interplay at gene expression level that contributes to the robustness/resilience of core metabolism, also promoting the use of state-of-the-art multi-disciplinary approaches to fully comprehend molecular adaptations to environmental fluctuations.

NMR-Based Metabolomics to Evaluate Individual Response to Treatments.

The aim of this chapter is to highlight the various aspects of metabolomics in relation to health and diseases, starting from the definition of metabolic space and of how individuals tend to maintain their own position in this space. Physio-pathological stimuli may cause individuals to lose their position and then regain it, or move irreversibly to other positions. By way of examples, mostly selected from our own work using 1H NMR on biological fluids, we describe the effects on the individual metabolomic fingerprint of mild external interventions, such as diet or probiotic administration. Then we move to pathologies (such as celiac disease, various types of cancer, viral infections, and other diseases), each characterized by a well-defined metabolomic fingerprint. We describe the effects of drugs on the disease fingerprint and on its reversal to a healthy metabolomic status. Drug toxicity can be also monitored by metabolomics. We also show how the individual metabolomic fingerprint at the onset of a disease may discriminate responders from non-responders to a given drug, or how it may be prognostic of e.g., cancer recurrence after many years. In parallel with fingerprinting, profiling (i.e., the identification and quantification of many metabolites and, in the case of selected biofluids, of the lipoprotein components that contribute to the 1H NMR spectral features) can provide hints on the metabolic pathways that are altered by a disease and assess their restoration after treatment.

2D NMR Analysis as a Sensitive Tool for Evaluating the Higher-Order Structural Integrity of Monoclonal Antibody against COVID-19.

The higher-order structure (HOS) of protein therapeutics has been confirmed as a critical quality parameter. In this study, we compared 2D 1H-13C ALSOFAST-HMQC NMR spectra with immunochemical ELISA-based analysis to evaluate their sensitivity in assessing the HOS of a potent human monoclonal antibody (mAb) for the treatment of coronavirus disease 2019 (COVID-19). The study confirmed that the methyl region of the 2D 1H-13C NMR spectrum is sensitive to changes in the secondary and tertiary structure of the mAb, more than ELISA immunoassay. Because of its highly detailed level of characterization (i.e., many 1H-13C cross-peaks are used for statistical comparability), the NMR technique also provided a more informative outcome for the product characterization of biopharmaceuticals. This NMR approach represents a powerful tool in assessing the overall higher-order structural integrity of mAb as an alternative to conventional immunoassays.

Comparative NMR metabolomics of the responses of A2780 human ovarian cancer cells to clinically established Pt-based drugs.

Pt-Based drugs play a very important role in current cancer treatments; yet, their cellular and mechanistic aspects are not fully understood. NMR metabolomics provides a powerful tool to investigate the metabolic perturbations induced by Pt drugs in cancer cells and decipher their meaning in relation to the presumed molecular mechanisms. We have carried out a systematic and comparative 1H NMR metabolomics study to analyze the responses of A2780 human ovarian cancer cells to the main clinically established Pt drugs, i.e., cisplatin, carboplatin and oxaliplatin. Notably, NMR analysis revealed some moderate and consistent changes in the metabolomic profiles of A2780 cells treated with the 3 Pt drugs with respect to controls, but only very small differences among them. Beyond alterations at the level of nucleic acid precursors, the observed changes highlight in all cases the induction of a significant endoplasmic reticulum stress. Owing to the clinical relevance of platinum resistance, the behavior of a cisplatin resistant A2780 cancer cell line upon cisplatin treatment was also evaluated.

Towards a mechanistic understanding of microalgae-bacteria interactions: integration of metabolomic analysis and computational models.

Interactions amongst marine microalgae and heterotrophic bacteria drive processes underlying major biogeochemical cycles and are important for many artificial systems. These dynamic and complex interactions span the range from cooperative to competitive, and it is the diverse and intricate networks of metabolites and chemical mediators that are predicted to principally dictate the nature of the relationship at any point in time. Recent advances in technologies to identify, analyze, and quantify metabolites have allowed for a comprehensive view of the molecules available for exchange and/or reflective of organismal interactions, setting the stage for development of mechanistic understanding of these systems. Here, we (i) review the current knowledge landscape of microalgal-bacterial interactions by focusing on metabolomic studies of selected, simplified model systems; (ii) describe the state of the field of metabolomics, with specific focus on techniques and approaches developed for microalga-bacterial interaction studies; and (iii) outline the main approaches for development of mathematical models of these interacting systems, which collectively have the power to enhance interpretation of experimental data and generate novel testable hypotheses. We share the viewpoint that a comprehensive and integrated series of -omics approaches that include theoretical formulations are necessary to develop predictive and mechanistic understanding of these biological entities.

Profiling metabolites and lipoproteins in COMETA, an Italian cohort of COVID-19 patients.

Metabolomics and lipidomics have been used in several studies to define the biochemical alterations induced by COVID-19 in comparison with healthy controls. Those studies highlighted the presence of a strong signature, attributable to both metabolites and lipoproteins/lipids. Here, 1H NMR spectra were acquired on EDTA-plasma from three groups of subjects: i) hospitalized COVID-19 positive patients (≤21 days from the first positive nasopharyngeal swab); ii) hospitalized COVID-19 positive patients (>21 days from the first positive nasopharyngeal swab); iii) subjects after 2-6 months from SARS-CoV-2 eradication. A Random Forest model built using the EDTA-plasma spectra of COVID-19 patients ≤21 days and Post COVID-19 subjects, provided a high discrimination accuracy (93.6%), indicating both the presence of a strong fingerprint of the acute infection and the substantial metabolic healing of Post COVID-19 subjects. The differences originate from significant alterations in the concentrations of 16 metabolites and 74 lipoprotein components. The model was then used to predict the spectra of COVID-19>21 days subjects. In this group, the metabolite levels are closer to those of the Post COVID-19 subjects than to those of the COVID-19≤21 days; the opposite occurs for the lipoproteins. Within the acute phase patients, characteristic trends in metabolite levels are observed as a function of the disease severity. The metabolites found altered in COVID-19≤21 days patients with respect to Post COVID-19 individuals overlap with acute infection biomarkers identified previously in comparison with healthy subjects. Along the trajectory towards healing, the metabolome reverts back to the "healthy" state faster than the lipoproteome.

Serum NMR Profiling Reveals Differential Alterations in the Lipoproteome Induced by Pfizer-BioNTech Vaccine in COVID-19 Recovered Subjects and Naïve Subjects.

1H NMR spectra of sera have been used to define the changes induced by vaccination with Pfizer-BioNTech vaccine (2 shots, 21 days apart) in 10 COVID-19-recovered subjects and 10 COVID-19-naïve subjects at different time points, starting from before vaccination, then weekly until 7 days after second injection, and finally 1 month after the second dose. The data show that vaccination does not induce any significant variation in the metabolome, whereas it causes changes at the level of lipoproteins. The effects are different in the COVID-19-recovered subjects with respect to the naïve subjects, suggesting that a previous infection reduces the vaccine modulation of the lipoproteome composition.

S1P Signalling Axis Is Necessary for Adiponectin-Directed Regulation of Electrophysiological Properties and Oxidative Metabolism in C2C12 Myotubes.

BACKGROUND: Adiponectin (Adn), released by adipocytes and other cell types such as skeletal muscle, has insulin-sensitizing and anti-inflammatory properties. Sphingosine 1-phosphate (S1P) is reported to act as effector of diverse biological actions of Adn in different tissues. S1P is a bioactive sphingolipid synthesized by the phosphorylation of sphingosine catalyzed by sphingosine kinase (SK) 1 and 2. Consolidated findings support the key role of S1P in the biology of skeletal muscle. METHODS AND RESULTS: Here we provide experimental evidence that S1P signalling is modulated by globular Adn treatment being able to increase the phosphorylation of SK1/2 as well as the mRNA expression levels of S1P4 in C2C12 myotubes. These findings were confirmed by LC-MS/MS that showed an increase of S1P levels after Adn treatment. Notably, the involvement of S1P axis in Adn action was highlighted since, when SK1 and 2 were inhibited by PF543 and ABC294640 inhibitors, respectively, not only the electrophysiological changes but also the increase of oxygen consumption and of aminoacid levels induced by the hormone, were significantly inhibited. CONCLUSION: Altogether, these findings show that S1P biosynthesis is necessary for the electrophysiological properties and oxidative metabolism of Adn in skeletal muscle cells.

Impact of the pre-examination phase on multicenter metabolomic studies.

The development of metabolomics in clinical applications has been limited by the lack of validation in large multicenter studies. Large population cohorts and their biobanks are a valuable resource for acquiring insights into molecular disease mechanisms. Nevertheless, most of their collections are not tailored for metabolomics and have been created without specific attention to the pre-analytical requirements for high-quality metabolome assessment. Thus, comparing samples obtained by different pre-analytical procedures remains a major challenge. Here, 1H NMR-based analyses are used to demonstrate how human serum and plasma samples collected with different operating procedures within several large European cohort studies from the Biobanking and Biomolecular Resources Infrastructure - Large Prospective Cohorts (BBMRI-LPC) consortium can be easily revealed by supervised multivariate statistical analyses at the initial stages of the process, to avoid biases in the downstream analysis. The inter-biobank differences are discussed in terms of deviations from the validated CEN/TS 16945:2016 / ISO 23118:2021 norms. It clearly emerges that biobanks must adhere to the evidence-based guidelines in order to support wider-scale application of metabolomics in biomedicine, and that NMR spectroscopy is informative in comparing the quality of different sample sources in multi cohort/center studies.

Modelling hCDKL5 Heterologous Expression in Bacteria.

hCDKL5 refers to the human cyclin-dependent kinase like 5 that is primarily expressed in the brain. Mutations in its coding sequence are often causative of hCDKL5 deficiency disorder, a devastating neurodevelopmental disorder currently lacking a cure. The large-scale recombinant production of hCDKL5 is desirable to boost the translation of preclinical therapeutic approaches into the clinic. However, this is hampered by the intrinsically disordered nature of almost two-thirds of the hCDKL5 sequence, making this region more susceptible to proteolytic attack, and the observed toxicity when the enzyme is accumulated in the cytoplasm of eukaryotic host cells. The bacterium Pseudoalteromonas haloplanktis TAC125 (PhTAC125) is the only prokaryotic host in which the full-length production of hCDKL5 has been demonstrated. To date, a system-level understanding of the metabolic burden imposed by hCDKL5 production is missing, although it would be crucial for upscaling of the production process. Here, we combined experimental data on protein production and nutrients assimilation with metabolic modelling to infer the global consequences of hCDKL5 production in PhTAC125 and to identify potential overproduction targets. Our analyses showed a remarkable accuracy of the model in simulating the recombinant strain phenotype and also identified priority targets for optimised protein production.